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Description
Apache Doris serves as a cutting-edge data warehouse tailored for real-time analytics, enabling exceptionally rapid analysis of data at scale.
It features both push-based micro-batch and pull-based streaming data ingestion that occurs within a second, alongside a storage engine capable of real-time upserts, appends, and pre-aggregation.
With its columnar storage architecture, MPP design, cost-based query optimization, and vectorized execution engine, it is optimized for handling high-concurrency and high-throughput queries efficiently.
Moreover, it allows for federated querying across various data lakes, including Hive, Iceberg, and Hudi, as well as relational databases such as MySQL and PostgreSQL.
Doris supports complex data types like Array, Map, and JSON, and includes a Variant data type that facilitates automatic inference for JSON structures, along with advanced text search capabilities through NGram bloomfilters and inverted indexes.
Its distributed architecture ensures linear scalability and incorporates workload isolation and tiered storage to enhance resource management.
Additionally, it accommodates both shared-nothing clusters and the separation of storage from compute resources, providing flexibility in deployment and management.
Description
Cribl Search introduces an innovative search-in-place technology that allows users to effortlessly explore, discover, and analyze data that was once deemed inaccessible, directly from its source and across various cloud environments, including data secured behind APIs. Users can easily navigate through their Cribl Lake or examine data stored in prominent object storage solutions such as AWS S3, Amazon Security Lake, Azure Blob, and Google Cloud Storage, while also enriching their insights by querying multiple live API endpoints from a variety of SaaS providers. The core advantage of Cribl Search is its strategic capability to forward only the essential data to analytical systems, thus minimizing the expenses associated with storage. With built-in compatibility for platforms like Amazon Security Lake, AWS S3, Azure Blob, and Google Cloud Storage, Cribl Search offers a unique opportunity to analyze all data directly where it resides. Furthermore, it empowers users to conduct searches and analyses on data regardless of its location, whether it be debug logs at the edge or data archived in cold storage, thereby enhancing their data-driven decision-making. This versatility in data access significantly streamlines the process of gaining insights from diverse data sources.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
Apache Flink
Apache Hudi
Apache Spark
Azure Blob Storage
Baidu Palo
Cribl AppScope
Cribl Edge
Cribl Lake
Cribl Stream
Integrations
Amazon S3
Apache Flink
Apache Hudi
Apache Spark
Azure Blob Storage
Baidu Palo
Cribl AppScope
Cribl Edge
Cribl Lake
Cribl Stream
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
The Apache Software Foundation
Founded
1999
Country
United States
Website
doris.apache.org
Vendor Details
Company Name
Cribl
Founded
2018
Country
United States
Website
cribl.io/search/
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Product Features
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery